Attention in Cognitive Systems: 5th International Workshop by Jonathan Harel, Christof Koch (auth.), Lucas Paletta, John

By Jonathan Harel, Christof Koch (auth.), Lucas Paletta, John K. Tsotsos (eds.)

This quantity constitutes the completely refereed post-workshop court cases of the fifth foreign Workshop on recognition in Cognitive platforms, WAPCV 2008, held in Fira, Santorini, Greece in may perhaps 2008 as an linked occasion of the sixth overseas convention on computing device imaginative and prescient platforms (ICVS 2008).

The thirteen revised complete papers awarded including with nine posters, were rigorously chosen from 34 submissions. The papers are geared up in topical sections on awareness in scene exploration, contextueal cueing and saliency, spatiotemporal saliency, attentional networks in addition to attentional modelling.

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Artificial Intelligence 146(1), 77–123 (2003) 10. : A proto-object based visual attention model. , Rome, E. ) WAPCV 2007. LNCS (LNAI), vol. 4840, pp. 198– 215. Springer, Heidelberg (2007) 11. : Visual indexes, preconceptual objects, and situated vision. Cognition 80(1–2), 127–158 (2001) 12. : Two selection stages provide efficient object-based attentional control for dynamic vision. In: Paletta, L. ) International Workshop on Attention and Performance in Computer Vision (WAPCV 2003). Joanneum Research, Graz (2003) 13.

6) i This energy function defines a winner-takes-all (WTA) behaviour, where Ii is the input and yi is the output of each unit. This energy function is minimal when all yi are zero except one, and when the corresponding input Ii has the maximal value of all inputs. Applied to the hand network where each finger map requires a WTA-behaviour, the first part of the equation turns into: 5 (f ) a (yij ) EWTA = (f ) yij − 1)2 . ( f =1 (7) ij The input part of the original WTA-equation was modified to take the geometrical constraints into account: 5 (f ) (f ) Ef (yij ) = − (f) wf · yij · Iij , (8) f =2 ij (1) (1) Et (yij ) = − (t) w1 · yij · Iij .

B which will be selected after five focusing steps. 5 Experimental Results In order to test the performance of the proposed model of visual attention, we have compared it with the model of Itti et al. [17], using the same database of images they use 1 . This database consists of 64 colour images which contain an emergency triangle [21]. Our results show that in 64% of the images a ‘preattentive object’ inside the emergency triangle is chosen as the most salient image region (see Fig. 5 for one example).

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